Building Analytic Device

ABSTRACT

An information analytic system including an extraction unit that interacts with a multi-layered digital representation of a building and extracts digital representation of mechanical and electrical devices from the digital representation, a correlation unit that correlates each mechanical and electrical device to at least one other mechanical and electrical device that is in mechanical or electrical communication with the mechanical or electrical device, and a rule application unit that applies at least one rule to each mechanical and electrical device based on the correlations to other devices.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/158,878, filed on May 19, 2016, which is a continuation of U.S.patent application Ser. No. 14/831,374, filed on Aug. 20, 2015, now U.S.Pat. No. 9,373,083, which is a continuation of U.S. patent applicationSer. No. 13/873,447, filed Apr. 30, 2013, now U.S. Pat. No. 9,141,912,which claims the benefit of and priority to U.S. Provisional PatentApplication No. 61/642,891, filed on May 4, 2012, all of which areincorporated by reference herein in their entirety.

BACKGROUND OF THE INVENTION

Automation systems are used to control different processes and monitordifferent environmental and operational conditions in a facility. Asautomation systems have gained wider acceptance, the size and breath ofthe environmental and operational conditions monitored has consistentlygrown. A conventional automation system can monitor and store thousandsof conditions.

Because of the expansion in the size of automation systems, analyzingthe information gathered by these systems has become difficult. Inaddition, the complexity of the interaction of different systemsoperating in facilities has increased the complexity of this analysis.Because of this added complexity, analytical models have been developedto assist in the analysis of the data stored in automation systems.However, these models require a professional, such as an engineer, toreview the information stored in the automation system to determineanalytical rules that can be applied to the automation system tostreamline the operation of the systems in the building.

Many times, the amount of data stored in a building automation systemmakes the cost of reviewing the information in the automation systemimpractical. Further, because of the large amount of data to review,many analytical rules that may be implemented are not apparent to theperson reviewing the data, and are never implemented. Accordingly, aneed exists for a system that can simplify the selection of operationalrules based on information provided by an automation system.

SUMMARY OF THE INVENTION

Various embodiments of the present disclosure provide an informationanalytic system including an information gathering unit configured togather at least one piece of information from at least one of aplurality of devices connected to a network, an information analysisunit configured to analyze the gathered information, and a rulegeneration unit configured to generate at least one rule based on theanalysis performed by the information analysis unit. The rule analysisunit is configured to analyze each generated rule to identify the rulesthat can be applied to the corresponding piece information, and to applythe identified rule to the corresponding piece of information. The ruleanalysis unit is also configured to analyze unapplied rules to determinewhat additional information is required to apply each unapplied rule toat least one piece of information.

Another embodiment includes an information analysis unit for analyzinginformation gathered from a network, the information analysis unitincludes a memory and a processor that execute an application. Theapplication gathers at least one piece of information from at least oneof a plurality of devices connected to the network, analyzes thegathered information, generates at least one rule based on the analysisof each piece of information, analyzes each generated rule to identifyeach rule that can be applied to a corresponding piece of information,applies each identified rule to the corresponding piece of information,and analyzes each unapplied rule to determine what additionalinformation is required to apply each unapplied rule to at least onepiece of information.

Other objects, features, and advantages of the disclosure will beapparent from the following description, taken in conjunction with theaccompanying sheets of drawings, wherein like numerals refer to likeparts, elements, components, steps, and processes.

BRIEF DESCRIPTION OF THE DRAWINGS

The features and advantages of aspects of the present invention willbecome more apparent from the detailed description set forth below whentaken in conjunction with the claims and drawings, in which likereference numbers indicate identical or functionally similar elements.

FIG. 1 is a block diagram of a building analytic system suitable for usewith the methods and systems consistent with the present invention;

FIG. 2A is a more detailed depiction of the analytic unit included inthe analytic system of FIG. 1;

FIG. 2B is a more detailed depiction of a user computer included in theanalytic system of FIG. 1;

FIG. 2C is a more detailed depiction of an automation unit included inthe analytic system of FIG. 1;

FIG. 3 depicts a plurality of automation units connected together on asubnetwork;

FIG. 4 depicts a schematic representation of the analytic unit includedin the analytic system of FIG. 1 requesting information from anautomation device connected to the network;

FIG. 5A depicts a floor plan showing an automation system and mechanicalsystem information;

FIG. 5B depicts the information storage unit of FIG. 2A storinginformation in a graph database;

FIG. 6 depicts a user interface that generates a predeterminedanalytical rule that is stored in the rule storage unit of FIG. 2A;

FIG. 7 depicts a schematic representation of the rule analysis unit ofFIG. 2A automatically generating a list of rules based on the pointsstored in the information storage unit;

FIG. 8A depicts an illustrative example of the rule analysis unit ofFIG. 2A storing rule information in the information storage unit;

FIG. 8B depicts a schematic representation of the rule analysis unitgenerating a list of inactive rules that may be cost effectivelyactivated;

FIG. 8C depicts a schematic of the information storage unit of FIG. 2Arelating the devices to a space in the building; and

FIG. 9 depicts another embodiment of the rule analysis unit of FIG. 1determining potential inactive rules that may be economically applied.

DETAILED DESCRIPTION

While the present invention is susceptible of embodiment in variousforms, there is shown in the drawings and will hereinafter be describeda presently preferred embodiment with the understanding that the presentdisclosure is to be considered an exemplification of the invention andis not intended to limit the invention to the specific embodimentillustrated.

FIG. 1 depicts a block diagram of a building analytic system 100suitable for use with the methods and systems consistent with thepresent invention. The building analytic system 100 comprises aplurality of computers 102 and 104 and a plurality of automation devices106 are shown each connected to one another via a network 108. Thenetwork 108 is of a type that is suitable for connecting the computers102 and 104 and automation devices 106 for communication, such as acircuit-switched network or a packet-switched network. Also, the network108 may include a number of different networks, such as a local areanetwork, a wide area network such as the Internet, telephone networksincluding telephone networks with dedicated communication links,connection-less network, and wireless networks. In the illustrativeexample shown in FIG. 1, the network 108 is the Internet. Each of thecomputers 102 and 104, and the automation device 106, shown in FIG. 1 isconnected to the network 108 via a suitable communication link, such asa dedicated communication line or a wireless communication link.

Computer 102 may serve as an analytic unit that includes an informationgathering unit 110, an information analysis unit 112, a rule generationunit 114, and a rule analysis unit 116. The number of computers and thenetwork configuration shown in FIG. 1 are merely an illustrativeexample. One having skill in the art will appreciate that the dataprocessing system may include a different number of computers 102 and104, automation devices 106, and networks 108. For example, computer 102may include the information gathering unit 110, as well as, theinformation analysis unit 112. Further, the rule analysis unit 116 mayreside on a different computer than computer 102.

FIG. 2A shows a more detailed depiction of the analytic unit 102. Theanalytic unit 102 comprises a central processing unit (CPU) 202, aninput output (I/O) unit 204, a display device 206, a secondary storagedevice 208, and a memory 210. The analytic unit 102 may further comprisestandard input devices such as a keyboard, a mouse, a digitizer, or aspeech processing means (each not illustrated).

The analytic unit 102's memory 210 includes a Graphical User Interface(GUI) 212 which is used to gather information from a user via thedisplay device 206 and I/O unit 204 as described herein. The GUI 212includes any user interface capable of being displayed on a displaydevice 206 including, but not limited to, a web page, a display panel inan executable program, or any other interface capable of being displayedon a computer screen. The secondary storage device 208 includes aninformation storage unit 214 and a rule storage unit 216. Further, theGUI 212 may also be stored in the secondary storage unit 208. In oneembodiment consistent with the present invention, the GUI 212 isdisplayed using commercially available hypertext markup language (HTML)viewing software such as, but not limited to, Microsoft InternetExplorer®, Google Chrome® or any other commercially available HTMLviewing software.

One having skill in the art will appreciate that the information storageunit 214 may be distributed across a different number of computers 102and 104, automation devices 106, and networks 108. For example, computer102 may include a portion of the information storage unit 214, andanother computer 102 connected to the network 108 may include anotherportion of the information storage unit 214.

FIG. 2B shows a more detailed depiction of user computer 104. Computer104 comprises a CPU 222, an I/O unit 224, a display device 226, asecondary storage device 228, and a memory 230. Computer 104 may furthercomprise standard input devices such as a keyboard, a mouse, adigitizer, or a speech processing means (each not illustrated).

The memory 230 in computer 104 includes a GUI 232 which is used togather information from a user via the display device 226 and I/O unit224 as described herein. The GUI 232 includes any user interface capableof being displayed on a display device 226 including, but not limitedto, a web page, a display panel in an executable program, or any otherinterface capable of being displayed on a computer screen. The GUI 232may also be stored in the secondary storage unit 228. In one embodimentconsistent with the present invention, the GUI 232 is displayed usingcommercially available HTML viewing software such as, but not limitedto, Microsoft Internet Explorer®, Google Chrome® or any othercommercially available HTML viewing software.

FIG. 2C depicts a more detailed depiction of an automation device 106.The automation device 106 includes a CPU 250, an I/O unit 252, asecondary storage unit 254, a memory 256 that includes a networkcommunication unit 258, and a subnetwork communication unit 260. The IOunit 252 is communicatively coupled to a plurality of sensors 266 andcontrol units 264. Each sensor 262 is configured to sense environmentalinformation and transmit the sensed information back to the IO unit 252.Each control unit 264 is electronically or mechanically coupled to adevice such that the control unit 264 converts a signal transmitted fromthe IO unit 252 into a signal capable of effecting the operation of thedevice coupled to the control unit 264. The sensors 266 and controlunits 264 may be coupled to the IO unit 252 via a wired or wirelessconnection.

The network communication unit 258 is configured to connect to thenetwork 108. The subnetwork communication unit 260 is configured toconnect to a second network (not shown), or subnetwork, to communicatewith other automation units 106. The subnetwork may be a networkoperating unit the TIA/EIA-485 protocol, TIA/EIA, 422 protocols, theTIA/EIA 232 protocol, or any other protocol capable of connecting to atleast one automation device 106. The automation device 106 maycommunicate with other automation devices 106 over the networkcommunication unit 258, or subnetwork communication unit 260, using anycommunication protocol including BACnet, Modbus, LONworks, Fieldbus,CANbus, Profibus, TCP/IP, Ethernet, or any other communication protocol.The automation device 106 may only include the subnetwork communicationunit 260 or both the network communication unit 258 and the subnetworkcommunication unit 260.

The automation device 106 may be, but is not limited to, a voice overinternet protocol (VOIP) phone, a network switching device, a buildingautomation control device, a lighting automation control device, atelephone switching device, an IP camera, a digital video recorder, orany other device capable of communicating over a network.

The automation device 106 may also include a point database 262 storedin the secondary storage unit 254. A point is defined as any virtualobject or real device coupled to the automation device 106. As anillustrative example, a temperature sensor that is mounted on a wall andwired into an automation device 106 represents a point. In addition, avariable stored in the memory 256 of the automation device, such as atemperature set point, is also considered to be a point herein.

FIG. 3 depicts a plurality of automation units 106 connected together.The plurality of automation units 106 are communicatively coupled to amaster automation device 300. The master automation device 300 isconfigured to convert information from the subnetwork for transport overthe network 108. Each of the automation units 106 is configured togather information on environmental conditions, and to controlmechanical and electrical devices that affect the monitoredenvironmental conditions. The master automation device 300 convertsrequests for information from the network 108 to a format suitable fortransport over the subnetwork, and gathers information from theautomation units 106 connected to the subnetwork to generate a responseto the request.

FIG. 4 depicts a schematic representation of the analytic unit 102requesting information from an automation device 106 connected to thenetwork 108. In step 402, a master automation device 300 coupled to thenetwork 108 receives a request for information from the analytic unit102. In step 404, the automation devices 106 determine the location inthe memory 256 of the master automation device 300, or the location onthe subnetwork, where the requested information is stored. In step 406,the master automation device 300 requests the information from the localmemory 256, or from the automation devices 106 connected to thesubnetwork. In step 408, each automation device 106 on the subnetworkreceives the request from the master automation device 300, andtransmits any information related to the request back to the masterautomation device 300. In step 410, the master automation device 300formats the response based on the requirements of the analytic unit 102.The format of the response may be based on information received from theanalytic unit 102 as part of the request. In step 412, the masterautomation device 300 transmits the response back to the analytic unit102.

FIG. 5A depicts a floor plan 500 showing the object name and controllername for each sensor. The floor plan 500 includes a plurality of rooms502. Each room includes a temperature sensor icon 504 with aninformation box 506 positioned next to the temperature sensor icon 504that indicates an automation device indicator 506 and a point nameindicator 508. Each point name indicator 508 is configured to match acorresponding point name stored in the memory 256 of the automationdevice 106 as indicated by the device indicator 506. The deviceindicators 506 are configured to match the names of the automationdevices 106 connected to the master automation device 300.

Each room on the floor plan 500 also includes a room name indicator 510.The room name indicator 510 indicates the name, and potentially the use,for each room shown on the floor plan 500. The floor plan 500 may alsoinclude a pressure sensing unit icon 512 positioned in an elevator shaft514. The pressure sensing unit icon 512 may include a device indicator506 and a point name indicator 508.

The floor plan 500 may be stored in a digital format in the memory 210of the analytic unit 102, or the memory 230 of a client device 104. Thedigital format may be viewable and editable in a drafting program suchas AutoCAD®, provided by AutoDesk Corp. of San Rafael, Calif. The filemay also be generated by a building information modeling (“BIM”)software package such as, but not limited to, CADMEP by Technical SalesInternational, or any other BIM software. The drafting and BIM softwareprograms are configured to store information pertaining to the design ofa building in different layers of the file. Each layer includesinformation such as location, operational parameters, dimensions, andother information of equipment depicted in the floor plan. Theinformation analysis unit 112 is configured to extract all informationincluding the room name indicator 510, device indicator 506, and pointname indicator 508 from each floor plan stored in the floor plan file,and to store the extracted information in the information storage unit214.

The information analysis unit 112 may also associate pieces ofinformation extracted from the file together based on the location,operation, physical connection, or logical connections of each piece ofinformation. As an illustrative example referring to FIG. 5A, theinformation analysis unit 112 may associate the point Office_103_T withthe VAV_103 automation device. The information analysis unit 112 mayassociate the VAV_103 automation device with a variable air volume (VAV)mechanical unit for room 103 (VAV_103), based on the informationextracted from the file. Further the information analysis unit 112 mayalso determine that VAV_103 is associated with a specific air handlingunit (AHU), and associate VAV_103 with the AHU. The information analysisunit 112 may determine the relationships between devices by extractingand analyzing information in the file, such as a schedule of devices, awiring diagram, a mechanical system flow diagram, or any other datastructure in the file that provides information on the relationshipsbetween devices on the floor plan.

The information analysis unit 112 may also extract informationpertaining to the configuration and relationships of the mechanical andelectrical systems in the building. As an illustrative example, theinformation analysis unit 112 may extract information pertaining to theheating, ventilating and air conditioning systems connected to eachroom. The information analysis unit 112 may extract the name andlocation of the AHU connected to office 103 via duct work, and storethis information in the information storage unit 214. The informationanalysis unit 112 may also create a relationship between each point anda mechanical or electrical device based on the information extractedfrom the file.

The information analysis unit 112 may also be configured to scan thefloor plan to identify the different pieces of mechanical and electricalequipment included on each floor plan. Data may be extracted from adrafting program using any known method including exporting theattributes of objects in the drafting program. As an illustrativeexample, the information analysis unit may extract a listing of allmechanical equipment objects in a drawing along with the attributes forthe mechanical equipment. The attributes of each object may beconfigured to store information pertaining to the relationship of theobject to other mechanical devices. As an illustrative example, theVAV_103 object may include attributes such as the connected air handlingunit object identifier, control system object name, or any otherattribute describing the interconnection between VAV_103 and othersystems in the facility.

The information analysis unit 112 may extract the information from adrafting program, such as AutoCAD, and import the information into theinformation storage unit 214 during initial configuration of the system.The information analysis unit 112 may create objects in the informationstorage unit 214 corresponding to the points displayed on the floor planand associate these objects with extracted location indicators andconnected mechanical equipment.

The information analysis unit 112 may also extract informationpertaining to the configuration and use of each space on the floor plan.As an illustrative example referring to FIG. 5A, the informationanalysis unit 112 may extract the dimensions, wall size and thickness,and direction of the windows for each office and store this informationin the information storage unit 214. The information analysis unit 112may also extract information on the operation of the mechanical andelectrical devices on the floor plan.

Once all the information is extracted from the floor plan 500, theinformation analysis unit 112 categorizes each point in the informationstorage unit 214 based on the value of the information, in the case ofan input, or the signal the point is generating, in the case of anoutput. The information analysis unit 112 may categorize each point inthe information storage unit 214 by presenting each point to a user ofthe information analysis unit 102 via the GUI 212. The informationanalysis unit 112 may also categorize the spaces defined in the file,such an office or a conference room, along with the characteristics ofthe space. The characteristics of a space may include the direction thespace faces, the dimensions of the space, the operational use for thespace, the anticipated or actual occupancy of the space, or any otherattribute that can attributed to the space. Further, the informationanalysis unit 112 may also identify any other data structure from theinformation and categorizes the identified data structures intopredefined categories.

FIG. 5B depicts the information storage unit 214 storing information ina graph database. A graph database is a known data structure that storesdata in a graph structure including nodes, edges, and properties. Agraph database allows for the interrelation of different nodes. Theinformation storage unit 214 may incorporate any known graph databaseincluding, but not limited to, Horton provided by Microsoft Corporationof Redmond Wash., Neo4j by Neo Technologies, or any other graph databasesoftware. The information storage unit 214 may store each piece ofinformation from the floor plan 500 as a node in a graph database. Theinformation analysis unit 112 may also relate each of the nodes togetherbased on physical and logical connections between each node.

Returning to FIG. 5B as an illustrative example, AHU_1 522, VAV_103 524,and VAV_103_T 526 are created as nodes in the information storage unit214. The information analysis unit 114 logically relates AHU_1 522 withVAV_103 by edge 528, because AHU_1 and VAV_103 are physically connectedby ductwork. VAV_103_T is logically related to VAV_103 by edge 530,because VAV_103_T controls the operation of VAV_103. In addition,VAV_103 is logically related to a “Mechanical Device” category 532 byedge 534, because VAV_103 is a mechanical air control device. AHU_1 isalso related to the “Mechanical Device” category 532 because AHU_1 isalso a mechanical device. Further, VAV_103 and VAV_103_T are related toa “3^(rd) Floor” category because both devices are physically located onthe third floor of the building.

The information analysis unit 112 continues to relate all points enteredinto the information storage unit 214 based on the physical location ofeach point, and the mechanical or electrical systems the point monitorsor controls. The information analysis unit 112 may extract a list andposition of all mechanical devices on each floor of a building, andrelate each mechanical device to points extracted from the file, and toother mechanical devices in the building. The system may perform thesame analysis for electrical devices in the building. Further, thesystem may relate extracted mechanical devices to extracted electricaldevices. The system may also assign different attributes to the edgesconnecting each node. As an illustrative example, for the AHU node, theconnecting edges may include model and manufacturer information for theAHU.

FIG. 6 depicts a user interface 600 that generates a predeterminedanalytical rule that is stored in the rule storage unit 216. The rulegeneration unit 114 allows a user to configure predefined rules that arestored in the rule storage unit 216. A predetermined rule represents aset of conditions that initiate an event when the conditions aresatisfied. The user interface allows a user to select a point type 602,based on the types of points stored in the information storage unit 214,a point value 604 to initiate an analysis or event, a device type 606associated with the point category to analyze in connection with pointcategory, another point 608 associated with the associated devicecategory, and a value 610 for the associated point that initiatesanalysis or an event. FIG. 7 depicts a schematic representation of therules analysis unit 116 automatically generating a list of rules basedon the points stored in the information storage unit 216. In step 702,the rule analysis unit 116 retrieves the conditions of a first rulestored in the rule storage unit 216. In step 704, the rule analysis unit116 requests a listing of points consistent with the point type includedin the rule. In step 706, the rule analysis unit 116 determines thepoints in the listing of points that are associated with the device typeof the rule.

In step 708, the rule analysis unit 116 determines if the deviceassociated with each point includes the associated point type for therule. In step 710, the rule analysis unit 226 determines whether theinformation required by the rule resides in the system. In step 712, ifall the information required by the rule resides in the informationstorage unit 214, the rule analysis unit 116 indicates that the rule inthe rule storage unit 216 is active, and begins logging the values ofthe points associated with the rule in the information storage unit 214over a predefined interval. In step 714, if all the information requiredby the rule does not reside in the information storage unit 214, therule analysis unit 116 indicates that the rule is inactive in the rulestorage unit 216. In step 716, the activated rules are display to a uservia the GUI 212.

The information gathering unit 110 generates a list of all pointsincluded in the active rules, and requests the values associated withthe point names from the automation devices 106 where the points reside.The information gathering unit 110 logs the values returned from theautomation devices 106 in the information storage unit 208. As the pointlog in the information storage unit 214 is updated by the informationgathering unit 110, the rule analysis unit 116 analyzes the pointinformation stored in the information storage unit 214 based on therule, or rules, associated with each point, and initiates events whenthe conditions of any of the associated rules are satisfied. An eventmay include the generation of a report, email, alarm, or any other typeof notification or action.

FIG. 8A depicts an illustrative example of the rule analysis unit 114storing rule information in the information storage unit 214. A rule Ais created that monitors the fan voltage on AHU1 and VAV_104_T. Thegraph database in the information storage unit 214 relates theAHU_1_FAN_VOLT point to the VAV_104_T point by edges 802 and 804respectively. The information storage unit 214 stores the information ina graph database such that each rule is related to all points associatedwith the rule. In addition, each rule may be associated with a locationin the building or to a specific device. Returning to FIG. 8A, rule A isalso associated with the 3^(rd) floor by edge 806. Rule A may also berelated to VAV_103_T by edge 808. Accordingly, a single rule may berelated to multiple points. The rule analysis unit 116 activates aspecific rule based on the relationship between points stored in thedatabase as they apply to the specific rule.

As an illustrative example using the information from FIG. 6, the ruleanalysis unit 116 may request a list of all air handling units that arerelated to a temperature sensor and a fan voltage. The rule will then beapplied to all of the related points satisfying this request aspreviously discussed.

FIG. 8B depicts a schematic representation of the rule analysis unit 116generating a list of inactive rules that may be cost effectivelyactivated. In step 852, the rule analysis unit 116 retrieves a list ofinactive rules from the rule storage unit 216. In step 854, the ruleanalysis unit 116 requests a listing of existing points that wouldpotentially satisfy each inactive rule. A point potentially satisfies arule if it satisfies any of the category requirements of the rule. UsingFIG. 6 as an example, a temperature sensor related to an air handlingunit would potentially satisfy a portion of the first rule in the listof FIG. 6.

In step 856, the rule analysis unit 116 analyzes each rule to determinewhat additional point information is required to satisfy a remainingportion of each rule. In determining that additional point informationrequired to satisfy a rule, the rule analysis unit 116 may compare thepoint categories associated with the points categories in the rule todetermine if the all of the point categories of the rule exist in thesystem for each device. As an illustrative example, the rule analysisunit 116 may compare the point categories for a first rule with thepoint categories associated with a specific air handling unit. If theair handling unit being analyzed does not include a point category inthe rule, the rule analysis unit 116 identifies the missing category andassociates the missing point category with the air handling unit beinganalyzed.

In step 858, the rule analysis unit 116 stores the required points listin the rule storage unit 216 along with the required location and/orrequired device connections for each point. Referring again to FIGS. 5Aand 6, if the fan voltage on AHU_1 is not installed, the rule analysisunit 116 would identify the fan voltage on AHU_1 as a missing point thatis required to satisfy the first rule in FIG. 6. The rule analysis unit116 would also determine that adding a fan voltage sensor to AHU_1 wouldallow for the activation of the first rule in FIG. 6 for VAV_103.

In step 860, the rule analysis unit 116 determines the points ondifferent devices that are common to multiple rules. Because therequired points are stored in a graph database that relates the pointsto devices and locations, the rule analysis unit 116 can generate a listof rules that can be activated by adding a single point. As anillustrative example referring to FIGS. 5A and 6, the first rule in FIG.6 requires AHU_1 have a fan voltage to be implemented. The addition of afan voltage on AHU_1 would allow for the activation of the first rule inFIG. 6 in relation to VAV_103 to VAV_114. In addition, the addition ofthe fan voltage on AHU_1 will also allow for the activation of thesecond rule in FIG. 6 in relation to the 3^(rd) floor. Accordingly, theaddition of a single point can have a very large impact on the number ofactivated rules.

In step 862, the rule analysis unit 116 may display a listing of missingpoints to add on each system, and the associated rules that may beactivated by the addition of the points. The rule analysis unit 116 mayconfigure the displayed information such that a user can view the numberof rules that may be activated by adding a missing point to a specificdevice. Accordingly, the user is able to determine the impact of addingadditional points to the automation system. The report may also generatean estimated cost to add each missing point, and the projected economicimpact of the activation of each rule. The cost estimation may beperformed using known estimating techniques, such as allocating a costbased on the point type, or any other estimating method.

The rule analysis unit 116 may also determine the cost savingsassociated with implementing a rule. The cost savings may be generatedbased on historical information from similar facilities that is storedin the information storage unit 214. The rule analysis unit 214 may alsocalculate the estimated time required to generate enough savings to paythe cost of installing an additional point.

The rule analysis unit 116 may assign a cost saving equation to eachrule or device stored in the information storage unit 214. The costsaving equation may be related to the overall operation of a singledevice or multiple devices. Each cost saving equation may also be storedand associated with an individual device. As an illustrative example, afan in an air handing unit may be assigned the following cost estimateequation: Cost Savings=0.745699872(Fan Horsepower)*(1 hour)*(Cost perkilowatt-hour). where the fan horsepower and cost per kilowatt hour arestored in the information storage unit 214. The rule analysis unit 116may assign cost saving values to each rule in the in the informationstorage unit 214. Returning to the example, the rule analysis unit 116may assign a value of minus one (1) hour of operation per day to a ruleassociated with the fan in the air handling unit, which represents areduction of one (1) hour to the total daily operation of the fan if therule is implemented. The value may be inputted by an end user or may beestimated based on data stored in the information storage unit 214.

To determine the cost savings to implement a rule associated with theair handling unit, the rule analysis unit 116 calculates the costsavings using the equation above to determine the cost of operation ofthe fan for one hour. The rule analysis unit 214 then calculates thenumber for fewer hours the fan would operate when the rule isimplemented. The number of fewer of hours may be determined by examiningschedules associated with the air handling unit that are gathered by theinformation gathering unit 110. The information may also be inputted bya user into the rule analysis unit 116. Returning to the illustrativeexample, if the fan is 50 horsepower and would operate for 1 hour lessper day (the −1 value) and the fan operates 365 days per year, the totalsavings at 0.07 cents per kilowatt would be calculated as: CostSavings=0.745699872(50 hp)*(1 hour)*(0.07 cents/KWh)*(365 hours)=$952.63per year.

The rule analysis unit 116 may display the estimated yearly cost savingsof implementing the rule on the GUI.

The rule analysis unit 116 may also assign cost savings resulting from areduction in maintenance, better operational efficiencies, and reducedoperation of other related systems for each rule. Each additional costsavings reduction may be assigned to each rule and calculated usinginformation stored in the information storage unit 214 or gathered froma user. While the example above illustrates the calculation of savingsfor a fan, the rule analysis unit 116 may determine cost savings for anyrule by utilizing cost saving equations and information stored in theinformation storage unit 214.

FIG. 8C depicts a schematic of the information storage unit 214 relatingthe devices to a space in the building. As an illustrative example,Office_103_T_526 is associated with the Office 103 850 on the floor planin FIG. 5A. Office 103 850 is also related to the office category 852indicating that the space is used as an office, and the North Facing 854category indicating that the Office 103 faces north. The informationanalysis unit 112 may also relate Office 103 850 to other attributesassociated with an office including occupancy of the office, thematerials used to construct the room, or any other attribute of theoffice or the building. Each office node may also be related to otheroffice nodes by floor or quadrant of a floor. Accordingly, point,mechanical device, electrical device, and space information can beinterrelated in the information storage unit 214.

FIG. 9 depicts another embodiment of the rule analysis unit 116determining potential inactive rules that may be economically applied.The rule analysis unit 116 may identify typical relationships betweendevices, points, and space information to determine the likelihood thata particular rule would be applied to a point or points. As anillustrative example, the rule analysis unit may identify theOffice_103_T as being a space temperature sensor that is associated withoffice 103, the office 103 being associated with an office category, andthe attribute north facing. The Office_103_T may also be associated withthe 3^(rd) floor category and to VAV_103 524.

Returning to FIG. 9, in step 902, the rule analysis unit 116 generates alist of devices, and selects a first device for analysis. In step 904,the rule analysis unit 116 determines each direct relationship for theselected device by querying the information storage unit 214. In step906, the rule analysis unit 116 identifies devices in the informationstorage unit 214 that are related to the same, or substantially similar,categories. In step 908, the rule analysis unit 116 compares therelationships of the identified devices with the relationships of theselected device. In step 910, the rule analysis unit 116 identifiesrelationships the identified device has established that are notestablished with the selected device. In step 912, the rule analysisunit 116 identifies rules related to the identified device that utilizethe relationships identified in step 910. In step 914, the rule analysisunit 116 displays a listing of inactive rules that are activated forsimilar devices. The display may also present a listing of points thatmust be installed to initiate the rule.

The rule analysis unit 116 may also determine the frequency with which arule is related to each identified device. As an illustrative example,if a rule is applied to half of the devices identified in step 906, therule analysis unit 116 may display the rule along with an indicationthat 50% of similar devices activate the rule.

The rule analysis unit 116 may perform the same analysis performed inFIG. 9 using a space identifier or point identifier in place of thedevice. As an illustrative example, the rule analysis unit 116 maydetermine the relationships attached to a specific room type andgenerate a list of rules based on the rules applied to similar roomtypes.

The rule analysis unit 116 may also present the rules used by a systemon a GUI where users may rate the effectiveness of each rule. Further,the rule analysis unit 116 may analyze comments made by users on theimplementation and effectiveness of each rule and utilize the gatheredcomments to rate each rule. As an illustrative example, the ruleanalysis unit 116 may generate a list of all active and inactive rulesand present the rules in a list displayed on a GUI. A user can then vieweach rule and assign an effectiveness value to each rule based on therule's effectiveness at the user's facility. Further, a user mayinteract with other users to generate conditions for implementing aspecific rule, the information required to implement a specific rule, ormodifications of a specific rule that may enhance the operation of therule. The rule analysis unit may be configured to create new rules, oradjust existing rules, based on the comments, and additionalinformation, provided by users.

In the present disclosure, the words “a” or “an” are to be taken toinclude both the singular and the plural. Conversely, any reference toplural items shall, where appropriate, include the singular.

From the foregoing it will be observed that numerous modifications andvariations can be effectuated without departing from the true spirit andscope of the novel concepts of the present invention. It is to beunderstood that no limitation with respect to the specific embodimentsillustrated is intended or should be inferred. The disclosure isintended to cover by the appended claims all such modifications as fallwithin the scope of the claims.

What is claimed:
 1. An information analytical system including: anextraction unit that interacts with a multi-layered digitalrepresentation of a building and extracts digital representations ofmechanical and electrical devices from the digital representation; acorrelation unit that correlates each mechanical and electrical deviceto at least one other mechanical and electrical device that is inmechanical or electrical communication with the mechanical or electricaldevice; and a rule application unit that applies at least one rule toeach mechanical and electrical device based on the correlations to otherdevices.
 2. The information analytical system of claim 1 wherein theextraction unit also extracts at least one digital representation of aroom in the building.
 3. The information analytical system of claim 2wherein at least one mechanical device is a temperature sensor in aroom.
 4. The information analytical system of claim 1 including aninterface unit that associates each mechanical and electrical devicewith an associated control device.
 5. The information analytical systemof claim 4 wherein the control device initiates at least one controlstrategy based on the rule applied.
 6. The information analytical systemof claim 1 wherein the correlation unit associates a cost with theapplication of the at least one rule.
 7. The information analyticalsystem of claim 1 wherein each of the at least one rule is categorizedbased on the type of correlation between the devices.
 8. The informationanalytical system of claim 1 wherein the multi-layer digitalrepresentation of the building is a computer aided drafting file.
 9. Theinformation analytical system of claim 8 wherein the multi-layer digitalrepresentation of the building includes descriptions of each mechanicaland electrical device.
 10. The information analytical system of claim 1wherein the wherein the multi-layer digital representation of thebuilding includes correlations between each mechanical and electricaldevice and a space.
 11. A method of analyzing building relatedinformation via an information analytical system, the method includingthe steps of: extracting a digital representation of mechanical andelectrical devices from the digital representation via an extractionunit that interacts with a multi-layered digital representation of abuilding; correlating each mechanical and electrical device to at leastone other mechanical and electrical device that is in mechanical orelectrical communication with the mechanical or electrical device; andapplying at least one rule to each mechanical and electrical devicebased on the correlations to other devices.
 12. The method of claim 11,further including the step of extracting at least one digitalrepresentation of a room in the building.
 13. The method of claim 12,wherein at least one mechanical device is a temperature sensor in aroom.
 14. The method of claim 11, further including the step ofassociating each mechanical and electrical device with an associatedcontrol device.
 15. The method of claim 14, further including the stepof initiating at least one control strategy based on the rule applied.16. The method of claim 11, further including the step of associating acost with the application of the at least one rule.
 17. The method ofclaim 11, further including the step of categorizing each rule based onthe type of correlation between the devices.
 18. The method of claim 11,wherein the multi-layer digital representation of the building is acomputer aided drafting file.
 19. The method of claim 18, wherein themulti-layer digital representation of the building includes descriptionsof each mechanical and electrical device.
 20. The method of claim 11,wherein the multi-layer digital representation of the building includescorrelations between each mechanical and electrical device and a space.